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Nesting Technique : It’s Effects on Preterm Cardiorespiratory Indicators
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Background: Premature infant born with immature body system, their organs are not ready for extra uterine life, and they are unable to deal with external stress, which could alter body functions such as cardio-respiratory function. In addition, poor muscle tone increases the chance of developing an abnormal posture. To reduce this instability, applying developmental care such as nesting is vital to promote cardio-respiratory stability, maintain position, and reduce stress in preterm.      Objectives: The study aims to assess the impact of the nesting technique on preterm cardio-respiratory parameters in various positions (supine, prone, and right lateral).       Methodology: The research used randomized controlled trial design. By simple random sampling technique was choose 60 preterm infant, and they were divided into four groups equally (supine, prone, right lateral, and control group). The cardio-respiratory parameters (heart rate, respiratory rate, and oxygen saturation) were measured before and after applying the nesting and positioning techniques for 3 consecutive days. Data were analyzed by Statistical Package for Social Sciences (SPSS) program.                                                                                  Results: The study results showed a significant difference in the mean score of cardio-respiratory after three days of nesting technique with lateral, supine, and prone position groups at p= 0.000. While the control group showed there was non-significant change in the mean score of HR, RR, and Spo2 at p > 0.05.          Conclusion: The Study concluded that the nesting technique was effective for stabilizing the cardio-respiratory parameters of preterm infants. The authors recommended routinely using nesting with the ideal position technique in preterm as a part of  developmental care at the neonatal intensive care unit

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Publication Date
Thu Oct 01 2020
Journal Name
Defence Technology
A novel facial emotion recognition scheme based on graph mining
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Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

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Publication Date
Wed May 17 2023
Journal Name
Journal Of Engineering
Effect of Metakaolin on Properties of Lightweight Porcelinate Aggregate Concrete
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Research in Iraq has expanded in the field of material technology involving the properties of the lightweight concrete using natural aggregate. The use of the porcelinate aggregate in the production of structural light concrete has a wide objective
and requires a lot of research to become suitable for practical application. In this work metakaolin was used to improve compressive strength of lightweight porcelinate concrete which usually have a low compressive strength about 17 MPa . The effect of metakaolin on compressive, splitting tensile, flexure strengths and modulus of elasticity of lightweight porcelinate concrete have been investigated. Many experiments were carried out by replacing cement with different percentages of
met

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
On Gradient Descent Localization in 3-D Wireless Sensor Networks
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Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

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Publication Date
Fri Jul 14 2023
Journal Name
Aip Conference Proceedings
Seismic impact on makhool earthdam in flood and drought seasons
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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
INFLUENCE OF AMBIENT TEMPERATURE ON STIFFNESS OF ASPHALT PAVING MATERIALS
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Asphalt pavement properties in Iraq are highly affected by elevated summer air temperatures. One of these properties is stiffness (resilient modulus). To explain the effect of air temperatures on stiffness of asphalt concrete, it is necessary to determine the distribution of temperatures through the pavement asphalt concrete layers. In this study, the distribution of pavement temperatures at three depths (2cm,7cm, 10cm) below the pavement surface is determined by using the temperature data logger instrument. A relationship for determining pavement temperature as related to depth and air temperature has been suggested. To achieve the objective of this thesis, the prepared specimens have been tested for indirect tension in accordance with

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Publication Date
Sat Oct 29 2022
Journal Name
Computers
Intelligent Robotic Welding Based on a Computer Vision Technology Approach
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Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Sat Oct 29 2022
Journal Name
Computers
Intelligent Robotic Welding Based on a Computer Vision Technology Approach
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Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

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Publication Date
Tue Jun 25 2024
Journal Name
Biomedical And Pharmacology Journal
Psidium guajava: A Review on Its Pharmacological and Phytochemical Constituents
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Psidium guajava, belonging to the Myrtaceae family, thrives in tropical and subtropical regions worldwide. This important tropical fruit finds widespread cultivation in countries like India, Indonesia, Syria, Pakistan, Bangladesh, and South America. Throughout its various parts, including fruits, leaves, and barks, guava boasts a rich reservoir of bioactive compounds that have been traditionally utilized as folkloric herbal medicines, offering numerous therapeutic applications. Within guava, an extensive array of Various compounds with antioxidative properties and phytochemical constituents are present, including essential oils, polysaccharides, minerals, vitamins, enzymes, triterpenoids, alkaloids, steroids, glycosides, tannins, fl

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Protective Effect of Cafestol on Doxorubicin-induced Genotoxicity in Rats
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Doxorubicin is an efficient antineoplastic agent that has a broad antitumour spectrum; however, its genotoxic adverse effects on normal cells can be produced through oxidative damage, and this limits its clinical application. Cafestol is a naturally-occurring diterpene in unfiltered coffee with noteworthy antioxidant, antimutagenic and anti-inflammatory activities.

The present study aimed to investigate the possible protective effect of cafestol against doxorubicin-induced chromosomal and DNA damage in rat bone marrow cells. Wistar

Albino rats of both sexes were administered cafestol (5mg/kg body weight once

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